1. Sampling units are selected by chance.
2. It is possible to pre-specify every potential sample of a given size that could be drawn from the population, as well as the probability of selecting each sample.
3. Every potential sample need not have the same probability of selection, but it is possible to specify the probability of selecting any particular sample of a given size.
4. This requires not only a precise definition of the target population, but also a general specification of the sampling frame. Because sample elements are selected by chance.
5. It is possible to determine the precision of the sample estimated of the characteristics of interest. Confidence intervals, which contain the true population value with a given level of certainty, can be calculated. This permits the researcher to make inferences of projections about the target population from which the sample was drawn. Probability sampling techniques are classified based on :
Element versus cluster sampling
Equal unit probability versus unequal probabilities
Unstratified versus stratified selection
Random versus systematic selection
Single-stage versus multistage techniques
2. It is possible to pre-specify every potential sample of a given size that could be drawn from the population, as well as the probability of selecting each sample.
3. Every potential sample need not have the same probability of selection, but it is possible to specify the probability of selecting any particular sample of a given size.
4. This requires not only a precise definition of the target population, but also a general specification of the sampling frame. Because sample elements are selected by chance.
5. It is possible to determine the precision of the sample estimated of the characteristics of interest. Confidence intervals, which contain the true population value with a given level of certainty, can be calculated. This permits the researcher to make inferences of projections about the target population from which the sample was drawn. Probability sampling techniques are classified based on :
Element versus cluster sampling
Equal unit probability versus unequal probabilities
Unstratified versus stratified selection
Random versus systematic selection
Single-stage versus multistage techniques